OntoEval: an Automated Ontology Evaluation System

Antonio Zaitoun, Tomer Sagi, Katja Hose

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)

Abstract

Developing semantically-aware web services requires comprehensive and accurate ontologies. Evaluating an existing ontology or adapting it is a labor-intensive and complex task for which no automated tools exist. Nevertheless, in this paper we propose a tool that aims at making this vision come true, i.e., we present a tool for the automated evaluation of ontologies that allows one to rapidly assess an ontology’s coverage of a domain and identify specific problems in the ontology’s structure. The tool evaluates the domain coverage and correctness of parent-child relations of a given ontology based on domain information derived from a text corpus representing the domain. The tool provides both overall statistics and detailed analysis of sub-graphs of the ontology. In the demo, we show how these features can be used for the iterative improvement of an ontology.
Original languageEnglish
Title of host publicationACM Web Conference 2023 - Companion of the World Wide Web Conference, WWW 2023
Number of pages4
PublisherAssociation for Computing Machinery
Publication date30 Apr 2023
Pages82–85
ISBN (Electronic)978-1-4503-9419-2
DOIs
Publication statusPublished - 30 Apr 2023
EventThe ACM Web Conference 2023 - Austin, United States
Duration: 30 Apr 20234 May 2023

Conference

ConferenceThe ACM Web Conference 2023
Country/TerritoryUnited States
CityAustin
Period30/04/202304/05/2023

Keywords

  • BERT
  • knowledge engineering
  • natural language processing
  • ontology

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